TL;DR **Article claims:** Towns saw an increase in Anti-Refugee attacks if the average ~~daily~~ Facebook use of that town was higher than for 84% of all people nationally.

That percentage is related to the number of people, not to the average ~~time spent on~~ **use of** Facebook. (Conditions apply, **see below**.)

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Long version:

I quickly browsed the scientific paper to find what they measured, but realized I would have to read it more or less in full to understand it fully. They have somehow used Germany’s most popular Facebook page (Nutella Germany) to gauge **general** Facebook use.

So I’ll just speculate

Suppose they managed to estimate the *time* spent on Facebook per user per day. Then they computed the average of that, arriving at a national average and an average per town.

Now, about the “standard deviation”: of course, the time a person spends on Facebook is usually not the average for the population, but how far off from the average are they?

One way to express that would be as a percentage of the average. Say the average is 2 hours and a person spends 2 hours 30 minutes. Then that would be 25% higher than the average.

That’s easy to understand intuitively. The problem is that it doesn’t say anything about how common it is to be 25% above the average value - and it depends on the average. So 30 minutes is 25% of 2 hours, but only 5% of 10 hours.

Another way is relating to the rest of the population. Pick a limit on either side of the average, and count how many people fall within this range. Say 50% use Facebook between 1:50 and 2:15 per day.

This is what the standard deviation describes. The standard deviation also factors in how the data is spread around the average, which is often a good thing.

When we don’t know the exact distribution, assuming normal distribution might be ok. In that case, one standard deviation means those 68% of people closest to the average (34% below, 34% above).

Being above one standard deviation means a person belongs to the 16% most active Facebook users, or that 84% of the people use Facebook less than that person.

In the report, those towns had an average use higher than what 84% of all the people (nationally) had. ~~That means they either had~~ **This could be the case if, for example, there was** a group of extremely active people or a larger part of their inhabitants fell within the 16% most active users as seen nation-wide.

Caveats:

- I have not looked into the actual measure of activity used in the report
- I have not looked into the actual distribution of the data, so those specific percentages may not apply
- I have not checked if claims in the article have support in the report
- Statistical correlation does not mean that one thing caused the other, there could be a hidden cause affecting both things